Distributional health and financial benefits of increased tobacco taxes in Colombia: results from a modelling study.

BACKGROUND: In Colombia, smoking is the second leading modifiable risk factor for premature mortality. In December 2016, Colombia passed a major tax increase on tobacco products in an effort to decrease smoking and improve population health. While tobacco taxes are known to be highly effective in reducing the prevalence of smoking, they are often criticised as being regressive in consumption. This analysis attempts to assess the distributional impact (across socioeconomic groups) of the new tax on selected health and financial outcomes. METHODS: This study builds on extended cost-effectiveness analysis methods to study the new tobacco tax in Colombia, and estimates, over a time period of 20 years and across income quintiles of the current urban population (80% of the country population), the years of life gained with smoking cessation and the increased tax revenues, all associated with a 70% relative price increase of the pack of cigarettes. Where possible, we use parameters that vary by income quintile, including price elasticity of demand for cigarettes (average of -0.44 estimated from household survey data). FINDINGS: Over 20 years, the tax increase would lead to an estimated 191 000 years of life gained among Colombia's current urban population, with the largest gains among the bottom two income quintiles. The additional annual tax revenues raised would amount to about 2%-4% of Colombia's annual government health expenditure, with the poorest quintiles bearing the smallest tax burden increase. CONCLUSIONS: The tobacco tax increase passed by Colombia has substantial implications for the country's population health and financial well-being, with large benefits likely to accrue to the two poorest quintiles of the population.

Non-technical health care quality and health system responsiveness in middle-income countries: a cross-sectional study in China, Ghana, India, Mexico, Russia, and South Africa.

BACKGROUND: While there is increasing recognition that the non-technical aspects of health care quality - particularly the inter-personal dimensions of care - are important components of health system performance, evidence from population-based studies on these outcomes in low- and middle-income countries is sparse. This study assesses these non-technical aspects of care using two measures: health system responsiveness (HSR), which quantifies the degree to which the health system meets the expectations of the population, and non-technical health care quality (QoC), for which we 'filtered out' these expectations. Pooling data from six large middle-income countries, this study therefore aimed to determine how HSR and QoC vary between countries and by individuals' sociodemographic characteristics within countries. METHODS: We pooled individual-level data, collected between 2007 and 2010, from nationally representative household surveys of (primarily) adults aged 50 years and older in China, Ghana, India, Mexico, Russia, and South Africa. The outcome measure was a binary indicator for a 'bad' rating (HSR: "very bad" or "bad" on a five-point Likert scale; QoC: a worse rating of one's own visit than that of the character in an anchoring vignette) on at least one of seven dimensions for the most recent primary care visit. RESULTS: 23 749 adults who reported to have sought primary care during the preceding 12 months were includedin the analysis. The proportion of participants who gave a bad rating for their last primary care visit on at least one of seven dimensions varied from 4.3% (95% confidence interval (CI) = 2.8-6.7) in China to 33.1% (95% CI = 23.6-44.2) in South Africa for HSR, and from 17.0% (95% CI = 11.4-24.5) in Russia to 50.8% (95% CI = 46.0-55.6) in Ghana for QoC. There was a strong negative association between increasing household wealth and both bad HSR and QoC in India and South Africa. CONCLUSIONS: Achieving universal health coverage (UHC) with good-quality health services ("effective UHC") will require efforts to improve HSR and QoC across the population in Ghana and South Africa. Additionally, a particular focus on raising HSR and QoC for the poorest population groups is needed in India and South Africa.